Answer:
[tex]\hat y= 18.5 +0.890(65)=76.35[/tex]
Step-by-step explanation:
For this case we have a linear model given by:
[tex]\hat y= 18.5 +0.890 X[/tex]
Where X= represent the height.
Y= represent the beats per minute
And the slope is given by [tex]\beta_1 =0.890[/tex] and the intercept [tex]\beta_0 =18.5[/tex]
We have the mean for x and y given also [tex]\bar X= 62.9[/tex] [tex]\bar Y= 73.4[/tex]
And in order to find the best predicted value we just need to replace the value of X= 65, and we got this:
[tex]\hat y= 18.5 +0.890(65)=76.35[/tex]
If we want a confidence interval for the response variable when the predictor variable is x, is given by this formula:
[tex]\hat y \pm \sqrt{1+\frac{1}{n} +\frac{(x-\bar X)^2}{(n-1)s^2_x}}[/tex]
And if we replace we got this:
[tex]76.35 \pm \sqrt{1+\frac{1}{100} +\frac{(65-62.9)^2}{(100-1)s^2_x}}[/tex]
But for this case since we don't have the deviation we can just express it like this.